This project walks through how you can create recommendations using Apache Spark machine learning. There are a number of jupyter notebooks that you can run on IBM Data Science Experience, and there a live demo of a movie recommendation web application you can interact with. The demo also uses IBM Message Hub (kafka) to push application events to…
Movie Recommendation System with Complete End-to-End Pipeline, Model Intregration & Web Application Hosted. It will also help you build similar projects.
Exposing several ports unnecessarily can be a security risk, by exposing ports there will be a channel for unsecured communications and unrestricted traffic. By creating a special networks for the containers to share, the host is isolated from the multiple containers utilized.
A movie recommendation system trained on the MovieLens 20 Million dataset. This system makes use of Collaborative filtering methods to come up with recommendations for a particular user.
All things Beer! Beer Educator and Recommender Web App | Deployed on GCP > https://alegorithm-fxljyqhslq-uc.a.run.app/ | UT Data Analysis and Visualization Nov 2019 - May 2020.
The PACKER AMI project can be defined as once the developer uploads the python application code to Github, the automation process will create a Docker image and uploads it to the Docker Hub, and further, an AMI will be created with packer having docker container provisioned with an image of python flask application from Docker Hub.
